Impact of Quantization Noise on CNN-based Joint Source-Channel Coding and Modulation

This paper investigated the impact of a quantizer in analog-to-digital and digital-to-analog converters in communication devices on image quality when using deep learning-based joint source-channel coding modulation (JSCCM) for image transmission. In recent years, JSCCM, which efficiently encodes im...

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Vydané v:	IEEE Consumer Communications and Networking Conference s. 465 - 468
Hlavní autori:	Matsumoto, Keigo, Inoue, Yoshiaki, Hara-Azumi, Yuko, Maruta, Kazuki, Nakayama, Yu, Hisano, Daisuke
Médium:	Konferenčný príspevok..
Jazyk:	English Japanese
Vydavateľské údaje:	IEEE 08.01.2023
Predmet:	deep learning Image coding Image communication Image quality Joint source-channel coding PSNR quantization Quantization (signal) Symbols Training
ISSN:	2331-9860
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